code: def test_DetectFittableAggregator(self):
      aggregator = EnsembleSklearnAggregator(
          model=GradientBoostingClassifier()
      )
  
      # Check return types
      aggregator.fit(self.real_anomalies, self.mts_anomalies1)
  
      # Check return types
      assert isinstance(
          aggregator.predict(self.mts_anomalies1), TimeSeries
      )
      assert isinstance(
          aggregator.predict([self.mts_anomalies1]),
          Sequence,
      )
      assert isinstance(
          aggregator.predict(
              [self.mts_anomalies1, self.mts_anomalies2]
          ),
          Sequence,
      )
  
file_path: darts/darts/tests/ad/test_aggregators.py
imports: from typing import Sequence
  import numpy
  import pytest
  from sklearn.ensemble import GradientBoostingClassifier
  from darts import TimeSeries
  from darts.ad.aggregators.and_aggregator import AndAggregator
  from darts.ad.aggregators.ensemble_sklearn_aggregator import EnsembleSklearnAggregator
  from darts.ad.aggregators.or_aggregator import OrAggregator
  from darts.models import MovingAverageFilter
label_desc: Use image node_id 2 for calling the TestADAggregators obj's underlying member method code with example usage: obj.test_DetectFittableAggregator() without return types